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Who cites Shashank Srivastava

1,298 citations of their works from 1,293 papers of our library (of the 141,840 whose bibliographies we read) · 191 with a page here, the most cited first · page 2 of 2 · 101–191 · ← Shashank Srivastava

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    GrIPS: Gradient-free, Edit-based Instruction Search for Prompting Large Language ModelsConference of the European Chapter of the Association for Computational Linguistics (EACL)Archiki Prasad, Peter Hase, Xiang Zhou, et al.2023 · 182 citations
    On Second Thought, Let's Not Think Step by Step! Bias and Toxicity in Zero-Shot ReasoningAnnual Meeting of the Association for Computational Linguistics (ACL)Omar Shaikh, Hongxin Zhang, William Held, et al.2023 · 180 citations
    Event Detection and Co-reference with Minimal SupervisionConference on Empirical Methods in Natural Language Processing (EMNLP)Haoruo Peng, Yangqiu Song, Dan Roth2016 · 180 citations
  1. Evaluating Large Language Models: A Comprehensive SurveyarXiv:2310.19736Zishan Guo, Renren Jin, Chuang Liu, et al.2023 · 178 citations
    LILA: A Unified Benchmark for Mathematical ReasoningConference on Empirical Methods in Natural Language Processing (EMNLP)Swaroop Mishra, Matthew Finlayson, Pan Lu, et al.2022 · 177 citations
    LINC: A Neurosymbolic Approach for Logical Reasoning by Combining Language Models with First-Order Logic ProversConference on Empirical Methods in Natural Language Processing (EMNLP)Theo X. Olausson, Alex Gu, Benjamin Lipkin, et al.2023 · 171 citations
  2. Survey on Factuality in Large Language Models: Knowledge, Retrieval and Domain-SpecificityarXiv:2310.07521Cunxiang Wang, Xiaoze Liu, Yuanhao Yue, et al.2023 · 170 citations
    Label Verbalization and Entailment for Effective Zero and Few-Shot Relation ExtractionConference on Empirical Methods in Natural Language Processing (EMNLP)Oscar Sainz, Oier Lopez de Lacalle, Gorka Labaka, et al.2021 · 167 citations
  3. Generative Representational Instruction TuningarXiv:2402.09906Niklas Muennighoff, Hongjin Su, Liang Wang, et al.2024 · 165 citations
  4. Reasoning with Language Model Prompting: A SurveyarXiv:2212.09597Shuofei Qiao, Yixin Ou, Ningyu Zhang, et al.2022 · 161 citations
  5. Orca 2: Teaching Small Language Models How to ReasonarXiv:2311.11045Arindam Mitra, Luciano Del Corro, Shweti Mahajan, et al.2023 · 160 citations
    LLMLingua-2: Data Distillation for Efficient and Faithful Task-Agnostic Prompt CompressionFindings of the Association for Computational LinguisticsZhuoshi Pan, Qianhui Wu, Huiqiang Jiang, et al.2024 · 159 citations
    DataComp-LM: In search of the next generation of training sets for language modelsConference on Neural Information Processing Systems (NeurIPS)Jeffrey Li, Alex Fang, Georgios Smyrnis, et al.2024 · 156 citations
    ReConcile: Round-Table Conference Improves Reasoning via Consensus among Diverse LLMsAnnual Meeting of the Association for Computational Linguistics (ACL)Justin Chen, Swarnadeep Saha, Mohit Bansal2024 · 154 citations
    Language Model Behavior: A Comprehensive SurveyComputational LinguisticsTyler A. Chang, Benjamin K. Bergen2024 · 148 citations
    Few-shot Fine-tuning vs. In-context Learning: A Fair Comparison and EvaluationFindings of the Association for Computational LinguisticsMarius Mosbach, Tiago Pimentel, Shauli Ravfogel, et al.2023 · 147 citations
  6. Phi-4-Mini Technical Report: Compact yet Powerful Multimodal Language Models via Mixture-of-LoRAsarXiv:2503.01743Microsoft, Abdelrahman Abouelenin, Atabak Ashfaq, et al.2025 · 145 citations
    Self-Evaluation Guided Beam Search for ReasoningConference on Neural Information Processing Systems (NeurIPS)Yuxi Xie, Kenji Kawaguchi, Yiran Zhao, et al.2023 · 145 citations
    Automatically Correcting Large Language Models: Surveying the Landscape of Diverse Automated Correction StrategiesTransactions of the Association for Computational Linguistics (TACL)Liangming Pan, Michael Saxon, Wenda Xu, et al.2024 · 140 citations
  7. Unleashing the Emergent Cognitive Synergy in Large Language Models: A Task-Solving Agent through Multi-Persona Self-CollaborationarXiv:2307.05300Zhenhailong Wang, Shaoguang Mao, Wenshan Wu, et al.2023 · 139 citations
  8. A Roadmap to Pluralistic AlignmentarXiv:2402.05070Taylor Sorensen, Jared Moore, Jillian Fisher, et al.2024 · 135 citations
    Self-Knowledge Guided Retrieval Augmentation for Large Language ModelsFindings of the Association for Computational LinguisticsYile Wang, Peng Li, Maosong Sun, et al.2023 · 135 citations
    InFoBench: Evaluating Instruction Following Ability in Large Language ModelsFindings of the Association for Computational LinguisticsYiwei Qin, Kaiqiang Song, Yebowen Hu, et al.2024 · 133 citations
  9. To CoT or not to CoT? Chain-of-thought helps mainly on math and symbolic reasoningarXiv:2409.12183Zayne Sprague, Fangcong Yin, Juan Diego Rodriguez, et al.2024 · 133 citations
    FLUTE: Figurative Language Understanding through Textual ExplanationsConference on Empirical Methods in Natural Language Processing (EMNLP)Tuhin Chakrabarty, Arkadiy Saakyan, Debanjan Ghosh, et al.2022 · 132 citations
    Exploring Collaboration Mechanisms for LLM Agents: A Social Psychology ViewAnnual Meeting of the Association for Computational Linguistics (ACL)Jintian Zhang, Xin Xu, Ningyu Zhang, et al.2024 · 131 citations
    Faithful Logical Reasoning via Symbolic Chain-of-ThoughtAnnual Meeting of the Association for Computational Linguistics (ACL)Jundong Xu, Hao Fei, Liangming Pan, et al.2024 · 129 citations
    ZeroSCROLLS: A Zero-Shot Benchmark for Long Text UnderstandingFindings of the Association for Computational LinguisticsUri Shaham, Maor Ivgi, Avia Efrat, et al.2023 · 129 citations
    Automatic Prompt Augmentation and Selection with Chain-of-Thought from Labeled DataFindings of the Association for Computational LinguisticsKashun Shum, Shizhe Diao, Tong Zhang2023 · 128 citations
    Deductive Verification of Chain-of-Thought ReasoningConference on Neural Information Processing Systems (NeurIPS)Zhan Ling, Yunhao Fang, Xuanlin Li, et al.2023 · 128 citations
  10. Scaling Down to Scale Up: A Guide to Parameter-Efficient Fine-TuningarXiv:2303.15647Vladislav Lialin, Vijeta Deshpande, Xiaowei Yao, et al.2023 · 128 citations
  11. Safety-Tuned LLaMAs: Lessons From Improving the Safety of Large Language Models that Follow InstructionsarXiv:2309.07875Federico Bianchi, Mirac Suzgun, Giuseppe Attanasio, et al.2023 · 124 citations
  12. Large Language Model Alignment: A SurveyarXiv:2309.15025Tianhao Shen, Renren Jin, Yufei Huang, et al.2023 · 123 citations
  13. Large Language Models Understand and Can be Enhanced by Emotional StimuliarXiv:2307.11760Cheng Li, Jindong Wang, Yixuan Zhang, et al.2023 · 114 citations
    Ground-Truth Labels Matter: A Deeper Look into Input-Label DemonstrationsConference on Empirical Methods in Natural Language Processing (EMNLP)Kang Min Yoo, Junyeob Kim, Hyuhng Joon Kim, et al.2022 · 113 citations
    LMMs-Eval: Reality Check on the Evaluation of Large Multimodal ModelsFindings of the Association for Computational LinguisticsKaichen Zhang, Bo Li, Peiyuan Zhang, et al.2025 · 110 citations
  14. Evaluating the Performance of Large Language Models on GAOKAO BenchmarkarXiv:2305.12474Xiaotian Zhang, Chunyang Li, Yi Zong, et al.2023 · 109 citations
  15. MMTEB: Massive Multilingual Text Embedding BenchmarkarXiv:2502.13595Kenneth Enevoldsen, Isaac Chung, Imene Kerboua, et al.2025 · 101 citations
  16. Inverse Scaling: When Bigger Isn't BetterarXiv:2306.09479 · Transactions on Machine Learning Research (TMLR), 10/2023, https://openreview.net/forum?id=DwgRm72GQFIan R. McKenzie, Alexander Lyzhov, Michael Pieler, et al.2023 · 99 citations
  17. WildBench: Benchmarking LLMs with Challenging Tasks from Real Users in the WildarXiv:2406.04770Bill Yuchen Lin, Yuntian Deng, Khyathi Chandu, et al.2024 · 95 citations
    Boosting Language Models Reasoning with Chain-of-Knowledge PromptingAnnual Meeting of the Association for Computational Linguistics (ACL)Jianing Wang, Qiushi Sun, Xiang Li, et al.2024 · 94 citations
    MAmmoTH2: Scaling Instructions from the WebConference on Neural Information Processing Systems (NeurIPS)Xiang Yue, Tuney Zheng, Ge Zhang, et al.2024 · 94 citations
  18. FLASK: Fine-grained Language Model Evaluation based on Alignment Skill SetsarXiv:2307.10928Seonghyeon Ye, Doyoung Kim, Sungdong Kim, et al.2023 · 94 citations
    LLMs Are Few-Shot In-Context Low-Resource Language LearnersConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Samuel Cahyawijaya, Holy Lovenia, Pascale Fung2024 · 92 citations
  19. INSTRUCTEVAL: Towards Holistic Evaluation of Instruction-Tuned Large Language ModelsarXiv:2306.04757Yew Ken Chia, Pengfei Hong, Lidong Bing, et al.2023 · 92 citations
    PyramidInfer: Pyramid KV Cache Compression for High-throughput LLM InferenceFindings of the Association for Computational LinguisticsDongjie Yang, Xiaodong Han, Yan Gao, et al.2024 · 91 citations
    WildTeaming at Scale: From In-the-Wild Jailbreaks to (Adversarially) Safer Language ModelsConference on Neural Information Processing Systems (NeurIPS)Liwei Jiang, Kavel Rao, Seungju Han, et al.2024 · 89 citations
    “My Answer is C”: First-Token Probabilities Do Not Match Text Answers in Instruction-Tuned Language ModelsFindings of the Association for Computational LinguisticsXinpeng Wang, Bolei Ma, Chengzhi Hu, et al.2024 · 89 citations
  20. TextGrad: Automatic "Differentiation" via TextarXiv:2406.07496Mert Yuksekgonul, Federico Bianchi, Joseph Boen, et al.2024 · 88 citations
    NLPositionality: Characterizing Design Biases of Datasets and ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Sebastin Santy, Jenny Liang, Ronan Le Bras, et al.2023 · 88 citations
  21. A Survey on Data Selection for Language ModelsarXiv:2402.16827Alon Albalak, Yanai Elazar, Sang Michael Xie, et al.2024 · 85 citations
    LLMs cannot find reasoning errors, but can correct them given the error locationFindings of the Association for Computational LinguisticsGladys Tyen, Hassan Mansoor, Victor Carbune, et al.2024 · 85 citations
    SeaEval for Multilingual Foundation Models: From Cross-Lingual Alignment to Cultural ReasoningConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Bin Wang, Zhengyuan Liu, Xin Huang, et al.2024 · 85 citations
    NL-Augmenter: A Framework for Task-Sensitive Natural Language AugmentationNorthern European Journal of Language TechnologyKaustubh Dhole, Varun Gangal, Sebastian Gehrmann, et al.2023 · 85 citations
    ORCA: A Challenging Benchmark for Arabic Language UnderstandingFindings of the Association for Computational LinguisticsAbdelRahim Elmadany, ElMoatez Billah Nagoudi, Muhammad Abdul-Mageed2023 · 83 citations
    Style Over Substance: Evaluation Biases for Large Language ModelsInternational Conference on Computational Linguistics (COLING)Minghao Wu, Alham Fikri Aji2025 · 77 citations
    KoBBQ: Korean Bias Benchmark for Question AnsweringTransactions of the Association for Computational Linguistics (TACL)Jiho Jin, Jiseon Kim, Nayeon Lee, et al.2024 · 77 citations
  22. PUB: A Pragmatics Understanding Benchmark for Assessing LLMs' Pragmatics CapabilitiesSettaluri Sravanthi, Meet Doshi, Pavan Tankala, et al.2024 · 75 citations
    MEGAVERSE: Benchmarking Large Language Models Across Languages, Modalities, Models and TasksConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Sanchit Ahuja, Divyanshu Aggarwal, Varun Gumma, et al.2024 · 74 citations
    AppWorld: A Controllable World of Apps and People for Benchmarking Interactive Coding AgentsAnnual Meeting of the Association for Computational Linguistics (ACL)Harsh Trivedi, Tushar Khot, Mareike Hartmann, et al.2024 · 73 citations
  23. INCLUDE: Evaluating Multilingual Language Understanding with Regional KnowledgearXiv:2411.19799Angelika Romanou, Negar Foroutan, Anna Sotnikova, et al.2024 · 73 citations
  24. AlignBench: Benchmarking Chinese Alignment of Large Language ModelsarXiv:2311.18743Xiao Liu, Xuanyu Lei, Shengyuan Wang, et al.2023 · 73 citations
    KMMLU: Measuring Massive Multitask Language Understanding in KoreanConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Guijin Son, Hanwool Lee, Sungdong Kim, et al.2025 · 72 citations
    MediQ: Question-Asking LLMs and a Benchmark for Reliable Interactive Clinical ReasoningConference on Neural Information Processing Systems (NeurIPS)Shuyue Stella Li, Vidhisha Balachandran, Shangbin Feng, et al.2024 · 70 citations
  25. Mixture-of-Experts Meets Instruction Tuning:A Winning Combination for Large Language ModelsarXiv:2305.14705Sheng Shen, Le Hou, Yanqi Zhou, et al.2023 · 69 citations
    Knowledge of Knowledge: Exploring Known-Unknowns Uncertainty with Large Language ModelsFindings of the Association for Computational LinguisticsAlfonso Amayuelas, Kyle Wong, Liangming Pan, et al.2024 · 66 citations
    Detecting Subevent Structure for Event Coreference ResolutionLanguage Resources and Evaluation Conference (LREC)Jun Araki, Zhengzhong Liu, Eduard Hovy, et al.2014 · 65 citations
  26. CValues: Measuring the Values of Chinese Large Language Models from Safety to ResponsibilityarXiv:2307.09705Guohai Xu, Jiayi Liu, Ming Yan, et al.2023 · 63 citations
  27. Exploring the Impact of Instruction Data Scaling on Large Language Models: An Empirical Study on Real-World Use CasesarXiv:2303.14742Yunjie Ji, Yong Deng, Yan Gong, et al.2023 · 62 citations
  28. Large Language Model Routing with Benchmark DatasetsarXiv:2309.15789Tal Shnitzer, Anthony Ou, Mirian Silva, et al.2023 · 61 citations
  29. CMB: A Comprehensive Medical Benchmark in ChinesearXiv:2308.08833Xidong Wang, Guiming Hardy Chen, Dingjie Song, et al.2023 · 54 citations
  30. Language acquisition: do children and language models follow similar learning stages?arXiv:2306.03586Linnea Evanson, Yair Lakretz, Jean-Rémi King2023 · 53 citations
  31. Beyond Chinchilla-Optimal: Accounting for Inference in Language Model Scaling LawsarXiv:2401.00448Nikhil Sardana, Jacob Portes, Sasha Doubov, et al.2024 · 51 citations
    Pragmatics in the Era of Large Language Models: A Survey on Datasets, Evaluation, Opportunities and ChallengesAnnual Meeting of the Association for Computational Linguistics (ACL)Bolei Ma, Yuting Li, Wei Zhou, et al.2025 · 49 citations
    Metaphor Understanding Challenge Dataset for LLMsAnnual Meeting of the Association for Computational Linguistics (ACL)Xiaoyu Tong, Rochelle Choenni, Martha Lewis, et al.2024 · 47 citations
  32. Transcending Scaling Laws with 0.1% Extra ComputearXiv:2210.11399Yi Tay, Jason Wei, Hyung Won Chung, et al.2022 · 41 citations
  33. Observational Scaling Laws and the Predictability of Language Model PerformancearXiv:2405.10938Yangjun Ruan, Chris J. Maddison, Tatsunori Hashimoto2024 · 30 citations
  34. Prediction of Arabic Legal Rulings using Large Language ModelsarXiv:2310.10260Adel Ammar, Anis Koubaa, Bilel Benjdira, et al.2023 · 27 citations
  35. The Quantization Model of Neural ScalingarXiv:2303.13506Eric J. Michaud, Ziming Liu, Uzay Girit, et al.2023 · 27 citations
    Construction Grammar Provides Unique Insight into Neural Language ModelsInternational Workshop on Construction Grammars and NLPLeonie Weissweiler, Taiqi He, Naoki Otani, et al.2023 · 26 citations
    Chinese Event Coreference Resolution: An Unsupervised Probabilistic Model Rivaling Supervised ResolversConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Chen Chen, Vincent Ng2015 · 20 citations
  36. Do Large Language Models Understand Word Senses?Domenico Meconi, Simone Stirpe, Federico Martelli2025 · 18 citations
    Dialogue Discourse Parsing as Generation: A Sequence-to-Sequence LLM-based ApproachAnnual Meeting of the Special Interest Group on Discourse and Dialogue (SIGDIAL)Chuyuan Li, Yuwei Yin, Giuseppe Carenini2024 · 11 citations
    Construction Grammar Evidence for How LLMs Use Context-Directed Extrapolation to Solve TasksInternational Workshop on Construction Grammars and NLPHarish Tayyar Madabushi, Claire Bonial2025 · 1 citation
    Beyond Simple Term Injection: Reasoning Models for Legal Translation in a Non-Dominant Language VarietyAnnual Conference of the European Association for Machine Translation (EAMT)Paolo Di Natale, Elena Chiocchetti, Marlies Alber, et al.2026
    EduBench: A Portuguese Benchmark for Open-Ended Discursive Question AnsweringLanguage Resources and Evaluation Conference (LREC)Pedro Henrique Paiola, Luís Gabriel Damiati Mendes, Bruno de Oliveira Monchelato, et al.2026
    Open-access Dataset on Acceptability Ratings of Korean Clausal Constructions by Humans and GPT ModelsLanguage Resources and Evaluation Conference (LREC)Gyu-Ho Shin, Soo-Hwan Lee, Chanyoung Lee2026
    Persona-Aware Evaluation of Cognitive Bias in LLMs: From Benchmark to Applied Decision-MakingLanguage Resources and Evaluation Conference (LREC)Katsumasa Yoshikawa, Junya Takayama, Takato Yamazaki2026
    Sentiment Analysis and Language Models for KwanyamaLanguage Resources and Evaluation Conference (LREC)Ndapa Nakashole2026
    ZIP: Quantifying Which Words Matter in Zero-Shot Instructional PromptsJoint Conference on Lexical and Computational Semantics (*SEM)Nikta Gohari Sadr, Sangmitra Madhusudan, Arash Asgari, et al.2026
    Complexity factors of language models in reading comprehension: a controlled experiment (Étude des facteurs de complexité des modèles de langage dans une tâche de compréhension de lecture à l'aide d'une expérience contrôlée sémantiquement)JEP-TALN-RECITAL (the French-speaking conferences on speech and natural language processing)Elie Antoine, Frederic Bechet, Géraldine Damnati, et al.2024

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